Around 52% of the population of India rely on farming for their livelihood which accounts for 17% of India’s GDP. Whilst most farmers are familiar with conventional farming practices, they are often ill positioned to promptly deal with diseases and plant infestations affecting their crops. Current advisory systems tend to be generic and are not tailored to specific plots or farms. This work comprises an agriculture advisory call center similar to a modern call center to provide an agriculture disease mitigation system. The information regarding an individual farm is collected using mobile phones. The image of diseased/infected crop is also captured using mobile phones and is made available to the expert to provide the advisory. To scale the advisory, an attempt is also made to automate the disease recognition process using image processing. Unfortunately, the photos taken will be sensitive to a number of factors including camera type and lighting incident on the scene. Ideally, the images would be processed in such a way as to provide the expert with a visual representation of the affected crops that reflects the true nature of the scene. We describe a framework for standardising the colour of plant images taken using both mobile phones and compact cameras within the context of the advisory system.

Sion Hannuna1, N. Anantrasirichai2, Swarna Subramanian3, Suma Prashant4, Ashok Jhunjhunwala5 and C. Nishan Canagarajah6
1University of Bristol, UK,2,6University of Bristol, UK,3,4IITM’s Rural Technology and Business Incubator, India,5Indian Institute of Technology Madras, India

Plants, Pathology, Colour, Characterisation, Agriculture Advisory, Disease Mitigation
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ICTACT Journal on Communication Technology
( Volume: 2 , Issue: 2 , Pages: 363-369 )
Date of Publication :
June 2011
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